IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v9y2020i1p64-d470475.html
   My bibliography  Save this article

Binary Programming Model for Rostering Ambulance Crew-Relevance for the Management and Business

Author

Listed:
  • Aleksandra Marcikic Horvat

    (Faculty of Economics Subotica, University of Novi Sad, 24000 Subotica, Serbia)

  • Branislav Dudic

    (Faculty of Management, Comenius University in Bratislava, 82005 Bratislava, Slovakia
    Faculty of Economics and Engineering Management, University Business Academy, 21000 Novi Sad, Serbia)

  • Boris Radovanov

    (Faculty of Economics Subotica, University of Novi Sad, 24000 Subotica, Serbia)

  • Boban Melovic

    (Faculty of Economics, University of Montenegro, 81000 Podgorica, Montenegro)

  • Otilija Sedlak

    (Faculty of Economics Subotica, University of Novi Sad, 24000 Subotica, Serbia)

  • Monika Davidekova

    (Faculty of Management, Comenius University in Bratislava, 82005 Bratislava, Slovakia)

Abstract

The nature of health care services is very complex and specific, thus delays and organizational imperfections can cause serious and irreversible consequences, especially when dealing with emergency medical services. Therefore, constant improvements in various aspects of managing and organizing provision of emergency medical services are vital and unavoidable. The main goal of this paper is the development and application of a binary programming model to support decision making process, especially addressing scheduling workforce in organizations with stochastic demand. The necessary staffing levels and human resources allocation in health care organizations are often defined ad hoc, without empirical analysis and synchronization with the demand for emergency medical services. Thus, irrational allocation of resources can result in various negative impacts on the financial result, quality of medical services and satisfaction of both patients and employees. We start from the desired staffing levels determined in advance and try to find the optimal scheduling plan that satisfies all significant professional and regulatory constraints. In this paper a binary programming model has been developed and implemented in order to minimize costs, presented as the sum of required number of ambulance crews. The results were implemented for staff rostering process in the Ambulance Service Station in Subotica, Serbia. Compared to earlier scheduling done ad hoc at the station, the solution of the formulated model provides a better and equable engagement of crews. The developed model can be easily modified and applied to other organizations with the same, stochastic, nature of the demand.

Suggested Citation

  • Aleksandra Marcikic Horvat & Branislav Dudic & Boris Radovanov & Boban Melovic & Otilija Sedlak & Monika Davidekova, 2020. "Binary Programming Model for Rostering Ambulance Crew-Relevance for the Management and Business," Mathematics, MDPI, vol. 9(1), pages 1-13, December.
    • Handle: RePEc:gam:jmathe:v:9:y:2020:i:1:p:64-:d:470475
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/9/1/64/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/9/1/64/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ernst, A. T. & Jiang, H. & Krishnamoorthy, M. & Sier, D., 2004. "Staff scheduling and rostering: A review of applications, methods and models," European Journal of Operational Research, Elsevier, vol. 153(1), pages 3-27, February.
    2. Mateo Restrepo & Shane Henderson & Huseyin Topaloglu, 2009. "Erlang loss models for the static deployment of ambulances," Health Care Management Science, Springer, vol. 12(1), pages 67-79, March.
    3. R. Bekker & A. Bruin, 2010. "Time-dependent analysis for refused admissions in clinical wards," Annals of Operations Research, Springer, vol. 178(1), pages 45-65, July.
    4. A. Bruin & R. Bekker & L. Zanten & G. Koole, 2010. "Dimensioning hospital wards using the Erlang loss model," Annals of Operations Research, Springer, vol. 178(1), pages 23-43, July.
    5. Elio Borgonovi & Paola Adinolfi & Rocco Palumbo & Gabriella Piscopo, 2018. "Framing the Shades of Sustainability in Health Care: Pitfalls and Perspectives from Western EU Countries," Sustainability, MDPI, vol. 10(12), pages 1-20, November.
    6. Baozhong Su & Gatwaza Hategekimana Thierry & Qihui Chen & Qiran Zhao, 2017. "The New Cooperative Medical Scheme and Self-Employment in Rural China," Sustainability, MDPI, vol. 9(2), pages 1-10, February.
    7. Giovanni Felici & Claudio Gentile, 2004. "A Polyhedral Approach for the Staff Rostering Problem," Management Science, INFORMS, vol. 50(3), pages 381-393, March.
    8. Gang Du & Xi Liang & Chuanwang Sun, 2017. "Scheduling Optimization of Home Health Care Service Considering Patients’ Priorities and Time Windows," Sustainability, MDPI, vol. 9(2), pages 1-22, February.
    9. Nabil Channouf & Pierre L’Ecuyer & Armann Ingolfsson & Athanassios Avramidis, 2007. "The application of forecasting techniques to modeling emergency medical system calls in Calgary, Alberta," Health Care Management Science, Springer, vol. 10(1), pages 25-45, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Amber Kunkel & Laura McLay, 2013. "Determining minimum staffing levels during snowstorms using an integrated simulation, regression, and reliability model," Health Care Management Science, Springer, vol. 16(1), pages 14-26, March.
    2. Yuta Kanai & Hideaki Takagi, 2021. "Markov chain analysis for the neonatal inpatient flow in a hospital," Health Care Management Science, Springer, vol. 24(1), pages 92-116, March.
    3. Amir Rastpour & Armann Ingolfsson & Bora Kolfal, 2020. "Modeling Yellow and Red Alert Durations for Ambulance Systems," Production and Operations Management, Production and Operations Management Society, vol. 29(8), pages 1972-1991, August.
    4. Jonas Ingels & Broos Maenhout, 2018. "The impact of overtime as a time-based proactive scheduling and reactive allocation strategy on the robustness of a personnel shift roster," Journal of Scheduling, Springer, vol. 21(2), pages 143-165, April.
    5. Broos Maenhout & Mario Vanhoucke, 2008. "Comparison and hybridization of crossover operators for the nurse scheduling problem," Annals of Operations Research, Springer, vol. 159(1), pages 333-353, March.
    6. Almehdawe, Eman & Jewkes, Beth & He, Qi-Ming, 2013. "A Markovian queueing model for ambulance offload delays," European Journal of Operational Research, Elsevier, vol. 226(3), pages 602-614.
    7. Yoon, Soovin & Albert, Laura A., 2021. "Dynamic dispatch policies for emergency response with multiple types of vehicles," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    8. Jens O. Brunner & Jonathan F. Bard & Jan M. Köhler, 2013. "Bounded flexibility in days‐on and days‐off scheduling," Naval Research Logistics (NRL), John Wiley & Sons, vol. 60(8), pages 678-701, December.
    9. Samantha L. Zimmerman & Alexander R. Rutherford & Alexa Waall & Monica Norena & Peter Dodek, 2023. "A queuing model for ventilator capacity management during the COVID-19 pandemic," Health Care Management Science, Springer, vol. 26(2), pages 200-216, June.
    10. Avishai Mandelbaum & Petar Momčilović & Yulia Tseytlin, 2012. "On Fair Routing from Emergency Departments to Hospital Wards: QED Queues with Heterogeneous Servers," Management Science, INFORMS, vol. 58(7), pages 1273-1291, July.
    11. Veneklaas, W. & Leeftink, A.G. & van Boekel, P.H.C.M. & Hans, E.W., 2021. "On the design, implementation, and feasibility of hospital admission services: The admission lounge case," Omega, Elsevier, vol. 100(C).
    12. Oyku Ahipasaoglu & Nesim Erkip & Oya Ekin Karasan, 2019. "The venue management problem: setting staffing levels, shifts and shift schedules at concession stands," Journal of Scheduling, Springer, vol. 22(1), pages 69-83, February.
    13. Hui Zhang & Thomas J. Best & Anton Chivu & David O. Meltzer, 2020. "Simulation-based optimization to improve hospital patient assignment to physicians and clinical units," Health Care Management Science, Springer, vol. 23(1), pages 117-141, March.
    14. Van den Bergh, Jorne & Beliën, Jeroen & De Bruecker, Philippe & Demeulemeester, Erik & De Boeck, Liesje, 2013. "Personnel scheduling: A literature review," European Journal of Operational Research, Elsevier, vol. 226(3), pages 367-385.
    15. Armann Ingolfsson & Susan Budge & Erhan Erkut, 2008. "Optimal ambulance location with random delays and travel times," Health Care Management Science, Springer, vol. 11(3), pages 262-274, September.
    16. Izady, N. & Worthington, D., 2011. "Approximate analysis of non-stationary loss queues and networks of loss queues with general service time distributions," European Journal of Operational Research, Elsevier, vol. 213(3), pages 498-508, September.
    17. Almehdawe, Eman & Jewkes, Beth & He, Qi-Ming, 2016. "Analysis and optimization of an ambulance offload delay and allocation problem," Omega, Elsevier, vol. 65(C), pages 148-158.
    18. Maenhout, Broos & Vanhoucke, Mario, 2010. "A hybrid scatter search heuristic for personalized crew rostering in the airline industry," European Journal of Operational Research, Elsevier, vol. 206(1), pages 155-167, October.
    19. David Rea & Craig Froehle & Suzanne Masterson & Brian Stettler & Gregory Fermann & Arthur Pancioli, 2021. "Unequal but Fair: Incorporating Distributive Justice in Operational Allocation Models," Production and Operations Management, Production and Operations Management Society, vol. 30(7), pages 2304-2320, July.
    20. Lucian-Ionel Cioca & Mihaela Laura Bratu, 2020. "Sustainability of Youth Careers in Romania—Study on the Correlation of Students’ Personal Interests with the Selected University Field of Study," Sustainability, MDPI, vol. 13(1), pages 1-15, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:9:y:2020:i:1:p:64-:d:470475. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.